spark-instrumented-optimizer/sql
hyukjinkwon edf5cc64e4 [SPARK-25460][SS] DataSourceV2: SS sources do not respect SessionConfigSupport
## What changes were proposed in this pull request?

This PR proposes to respect `SessionConfigSupport` in SS datasources as well. Currently these are only respected in batch sources:

e06da95cd9/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala (L198-L203)

e06da95cd9/sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala (L244-L249)

If a developer makes a datasource V2 that supports both structured streaming and batch jobs, batch jobs respect a specific configuration, let's say, URL to connect and fetch data (which end users might not be aware of); however, structured streaming ends up with not supporting this (and should explicitly be set into options).

## How was this patch tested?

Unit tests were added.

Closes #22462 from HyukjinKwon/SPARK-25460.

Authored-by: hyukjinkwon <gurwls223@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2018-09-20 20:22:55 +08:00
..
catalyst Revert [SPARK-19355][SPARK-25352] 2018-09-20 20:18:31 +08:00
core [SPARK-25460][SS] DataSourceV2: SS sources do not respect SessionConfigSupport 2018-09-20 20:22:55 +08:00
hive Revert [SPARK-19355][SPARK-25352] 2018-09-20 20:18:31 +08:00
hive-thriftserver [SPARK-25436] Bump master branch version to 2.5.0-SNAPSHOT 2018-09-15 16:24:02 -07:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

Spark SQL

This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.

Spark SQL is broken up into four subprojects:

  • Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
  • Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
  • Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow users to run queries that include Hive UDFs, UDAFs, and UDTFs.
  • HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.